Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 41,
  • Issue 4,
  • pp. 1104-1113
  • (2023)

End-to-End Real-Time Service Provisioning Over a SDN-Controllable Analog mmWave Fiber -Wireless 5G X-Haul Network

Not Accessible

Your library or personal account may give you access

Abstract

The current work presents the first experimental demonstration of real-time Ethernet (ETH) trial services and 4K-Ultra High Definition (UHD) video application transmission over a 2λ Wavelength Division Multiplexing (WDM) analog Fiber-Wireless (FiWi) mmWave X-haul network, supporting dynamic flexible capacity allocation through an integrated silicon photonic Si3N4 Reconfigurable Optical Add Drop Multiplexer (ROADM) and 60 GHz wireless transmission across a 7 m V-band link distance, while controlled by a Software Defined Network (SDN) controller based on Open Daylight. Analog X-haul transport of the radio signals is based on an Intermediate Frequency over Fiber (IFoF) scheme centered at 1.5 GHz using an Orthogonal Frequency Division Multiplexing (OFDM) radio-waveform with a bandwidth of 204 MHz, generated by a Field Programmable Gated Array (FPGA)-based RF System-on-Chip (SoC) processor that converts on-the-fly the real-time ETH downlink traffic to analog radio and vice-versa for the uplink. Dynamic allocation of the X-haul traffic capacity is handled through the use of the 802.1Q Virtual Local Area Network (VLAN) tag-mechanism, which controls the forwarding operation to the proper DAC and InP EML for optical modulation using Intensity Modulation/Direct Detection (IM/DD) schemes, while the wavelength routing operation is handled by the low-loss four-port Si3N4 ROADM featuring only 2.5 dB fiber-to-fiber losses based on a cascaded MZI-interleaver design on the TriPleX platform, routing the real-time traffic to a second mmWave antenna site. Detailed measurements and traffic statistics indicate end-to-end latency of less than 260 μs and a packet loss less than 0.0054% across a dynamic range of at least 6.5 dB in the optical domain, while the high user bandwidth and signal quality are validated by an uninterrupted 4K-UHD video transmission across the FiWi X-haul mmWave transport network. The current work aims to shape a complete technology roadmap for Point-to-Multipoint FiWi transport network architectures with high spectral efficiency X-haul transport for dense areas and 5G/6G hotspots of future mmWave Centralized Radio Access Networks (C-RANs).

PDF Article
More Like This
Analog fiber-wireless downlink transmission of IFoF/mmWave over in-field deployed legacy PON infrastructure for 5G fronthauling

K. Kanta, A. Pagano, E. Ruggeri, M. Agus, I. Stratakos, R. Mercinelli, C. Vagionas, P. Toumasis, G. Kalfas, G. Giannoulis, A. Miliou, G. Lentaris, D. Apostolopoulos, N. Pleros, D. Soudris, and H. Avramopoulos
J. Opt. Commun. Netw. 12(10) D57-D65 (2020)

Live demonstration of an SDN-reconfigurable, FPGA-based TxRx for an analog-IFoF/mmWave radio access network in an MNO’s infrastructure

K. Kanta, P. Toumasis, G. Giannoulis, I. Stratakos, G. Lentaris, E. A. Papatheofanous, I. Mesogiti, E. Theodoropoulou, A. Margaris, D. Syrivelis, E. Kyriazi, G. Brestas, K. Tokas, N. Argyris, C. Vagionas, R. Maximidis, P. Bakopoulos, A. Mesodiakaki, M. Gatzianas, G. Kalfas, K. Tsagkaris, N. Pleros, D. Reisis, G. Lyberopoulos, D. Apostolopoulos, D. Soudris, and H. Avramopoulos
J. Opt. Commun. Netw. 15(8) C299-C306 (2023)

Converged Optical, Wireless, and Data Center Network Infrastructures for 5G Services

Anna Tzanakaki, Markos P. Anastasopoulos, and Dimitra Simeonidou
J. Opt. Commun. Netw. 11(2) A111-A122 (2019)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.